Estimating a monthly serverless bill

You need four numbers: requests per month, average input tokens per request, average output tokens per request, and the two rates for the model. Everything else follows from them.

Multiply requests by input tokens and divide by one million. Multiply by the input rate. Do the same for output. Add the two.

Guessed token counts are usually low. Real requests carry instructions, history and retrieved text that a guess forgets. Send a few hundred real requests and read the token counts the API returns with each response.

Use the average for the estimate and note the largest. The largest tells you what context window and output limit you need.

Three things grow a bill faster than traffic. Chat history, because each turn resends the turns before it. Retries, because a failed or cut-off request is paid for and then sent again. And reasoning, because a model that thinks before it answers bills that thinking as output.

Agents combine all three. A task that takes twenty steps sends its growing history twenty times.

Run the same sum for each model you are considering. On 12 Nov 2026, the lowest listed input price for Qwen3.8 27B was $0.035 per million tokens. The lowest listed output price was $0.395 per million tokens.

A smaller model at a lower rate is only a saving if it does the task. Check the answers before the arithmetic.

Runcrate charges every model to one prepaid balance, so a month’s use across models is one figure. Runcrate lists Qwen3.8 27B at $0.158 per million input tokens and $1.97 per million output tokens. Its API is OpenAI-compatible, so the client that logs your token counts today keeps working.

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